PyTorch torchvision up to 0.28.0 GIF decoder read_from_tensor out-of-bounds

Summaryinfo

A vulnerability classified as critical was found in PyTorch torchvision up to 0.28.0. The impacted element is the function read_from_tensor of the component GIF decoder. Executing a manipulation can lead to out-of-bounds. The identification of this vulnerability is CVE-2026-65918. The attack may be launched remotely. There is no exploit available.

Detailsinfo

A vulnerability has been found in PyTorch torchvision up to 0.28.0 and classified as critical. This vulnerability affects the function read_from_tensor of the component GIF decoder. The manipulation with an unknown input leads to a out-of-bounds vulnerability. The CWE definition for the vulnerability is CWE-125. The product reads data past the end, or before the beginning, of the intended buffer. As an impact it is known to affect confidentiality, integrity, and availability. CVE summarizes:

PyTorch torchvision through 0.28.0, fixed in commit 4e05dc2, contains an out-of-bounds heap read vulnerability in the GIF decoder's read_from_tensor callback that passes unclamped length to memcpy. Attackers can supply malicious or truncated GIF files to cause denial of service via segmentation fault or disclose adjacent heap memory contents.

The advisory is available at github.com. This vulnerability was named CVE-2026-65918 since 07/23/2026. The exploitation appears to be easy. The attack can be initiated remotely. Technical details are known, but there is no available exploit.

Applying the patch 4e05dc22f5f050a9528cc0ea09ceca6cdaf8f4ed is able to eliminate this problem.

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Productinfo

Vendor

• PyTorch

Name

• torchvision

Version

• 0.1
• 0.2
• 0.3
• 0.4
• 0.5
• 0.6
• 0.7
• 0.8
• 0.9
• 0.10
• 0.11
• 0.12
• 0.13
• 0.14
• 0.15
• 0.16
• 0.17
• 0.18
• 0.19
• 0.20
• 0.21
• 0.22
• 0.23
• 0.24
• 0.25
• 0.26
• 0.27
• 0.28.0

CPE 2.3info

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CPE 2.2info

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• 🔒
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Entryinfo

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